【摘要】 针对风光储接入配电网的位置与容量配置问题，本文提出一种基于灵敏度分析-改进遗传算法的风光储配置方法。建立了配电网网损灵敏度的模型，并根据灵敏度模型确定风光储的接入位置。通过改进遗传算法，在灵敏度模型确定位置的基础上进行容量的配置。利用风光发电互补的特征，以总出力波动最小为目标对风电和光伏的容量进行配置，再利用分时段配置方法对储能电池容量进行配置，进一步抑制风光出力波动。上述方法有效减少风光的出力波动，使风光储的配置满足电网的安全运行需求，同时加快了配置算法的求解速度。对IEEE 33节点系统进行算例分析，验证本方法可以有效降低网损，相较于传统遗传算法求解，具有更快的求解速度。更多还原

【Abstract】 Aiming at the problem of location and capacity allocation of wind and solar storage connected to distribution network, this paper proposes a method of wind, solar and storage allocation based on sensitivity analysis and improved genetic algorithm. A model of distribution network loss sensitivity is established, and the access location of wind, solar and storage are determined according to the sensitivity model. Through improved genetic algorithm, the capacity is configured based on the location determined by the sensitivity model. Based on the complementary characteristics of wind and solar power generation, the capacity of wind power and photovoltaic power is configured with the goal of minimizing the total output fluctuation, and then the capacity of energy storage battery is configured with the time-phased configuration method to further restrain the fluctuation of wind and solar power output. The above methods can effectively reduce the output fluctuation of wind and solar energy, make the configuration of wind, solar and storage meet the requirements of safe operation of the grid, and accelerate the solution speed of the configuration algorithm. An example of IEEE 33-bus system is analyzed to verify that this method can effectively reduce the network loss and has a faster solution speed compared with the traditional genetic algorithm.更多还原